In the oil and gas industry, geophysical prospecting techniques are typically used to aid in the search for and evaluation of subterranean hydrocarbon deposits. Many of these geophysical prospecting techniques utilize an impulsive seismic source, such as dynamite or a marine air gun, to generate a seismic signal which propagates into the earth and is at least partially reflected by subsurface seismic reflectors (i.e., interfaces between underground formations having different acoustic impedances). The reflections are recorded by seismic detectors located at or near the surface of the earth, in a body of water, or at known depths in boreholes, and the resulting seismic data may be processed to yield information relating to the location of the subsurface reflectors and the physical properties of the subsurface formations.
The objective of all seismic data processing is to extract from the data as much information as possible regarding the subsurface formations. This objective could best be achieved if the energy propagated into the earth were truly an impulse. As will be well known to those skilled in the art, an idealized, true impulse is one which has zero time duration and contains all frequencies from zero to infinity in equal strength and at zero phase. The reflected signal would then be referred to as the true "impulse response" of the earth (i.e., the response of the earth to the input of an impulse). Such an idealization can, of course, never be actually achieved. In practice, the signal that is typically imparted into the earth by an impulsive source has a short time duration (i.e., a few milliseconds) and is band-limited (i.e., contains all frequencies up to some upper limit), but with the higher frequencies attenuated relative to the lower ones.
The actual signal recorded by the seismic detectors can be represented as a convolution of the signal that is actually imparted into the earth with the desired impulse response of the earth and a number of other filtering actions or events, such as multiple reflections, which altered the signal as it propagated through the earth from the source to the detector. In order to properly interpret the data, the desired impulse response of the earth must be separated from the recorded signal, and the objectionable effects of the other filtering actions must be removed. The process for doing so is generally called "deconvolution" and has been practiced for many years. There are several different types of deconvolution, two of which, "adaptive" deconvolution (also known as "statistical" or "predictive" deconvolution)and "deterministic" deconvolution, are further described below.
The deconvolution typically used in conventional processing of seismic data from an impulsive source is an adaptive deconvolution in which the deconvolution filter is derived, in either the time domain or the frequency domain, from an estimate of the bandwidth of the signal imparted into the earth. In other words, the bandwidth of the signal is estimated from the recorded data and a deconvolution filter is derived that can be applied to the data to give an estimate of the impulse response of the earth. This process is also called, among other things, a spiking deconvolution, adaptive whitening, and adaptive signal shortening.
Adaptive deconvolution is also used in a variety of other seismic data processing applications. For example, in marine seismic prospecting the energy propagated into the earth is the direct downgoing energy as well as a delayed version of the original signal (i.e., a ghost signal) produced by reflection of upgoing energy from the water surface. In this situation, the resulting seismic data will include both reflections of the actual signal and reflections of the ghost signal. Adaptive deconvolution can be used to design a "deghosting" filter to remove the ghost reflections from the data. Another problem in marine seismic prospecting is the ringing or reverberation of energy within the water layer. The process of removing these reverberations from the data (dereverberation) is accomplished by an adaptive deconvolution.
In contrast with adaptive deconvolution, the process of deterministic deconvolution makes use of a known source spectrum. Instead of estimating the source spectrum from the recorded data, actual measurements of the outgoing signal may be made on designated monitors. Using this measured signal and the recorded data, it is possible to determine what the reflected signal would have been if the input signal had been a true impulse. See, Arya and Holden, "A Geophysical Application: Deconvolution of Seismic Data", pp 324-338 of Digital Signal Processing, Western Periodicals Co., N. Hollywood, Calif., 1979. This deterministic deconvolution may then be followed by an adaptive deconvolution to compensate for some of the other effects discussed earlier.
The deterministic deconvolution process disclosed by Arya and Holden has certain disadvantages which limit its utility. Measurement of the outgoing signal is expensive and, in some environments, such as a shallow water marine environment, can be very difficult to do. Furthermore, additional processing has to be done to the signal recorded on the monitors before a deconvolution filter can be derived. This is because the signal recorded by the monitors has to be corrected for the source radiation pattern, ghosting, and other effects resulting from its passage through the medium between the source and the monitor.
In the late 1950s and early 1960s, Conoco Inc. pioneered development of a new type of geophysical prospecting technique, generally known as "vibroseis" prospecting. Vibroseis prospecting employs a land or marine seismic vibrator rather than an impulsive energy source. The seismic vibrator is used to generate a controlled wavetrain which propagates through the earth to the seismic detectors. Typically, a sinusoidal vibration of continuously varying frequency is applied to the surface of the earth (or in the body of water) during a sweep period lasting from two to 20 seconds or even more. The frequency may be varied linearly or nonlinearly with time. Also, the frequency may begin low and increase with time (upsweep), or it may begin high and gradually decrease (downsweep).
Recently, a new type of signal known as a "shaped-sweep" has been developed for use in vibroseis prospecting. This shaped-sweep technology is disclosed in co-pending U.S. patent application Ser. No. 08/086776 filed Jul. 1, 1993. One benefit of using a shaped-sweep is that the sweep is designed to have an optimum pulse length and a desirable impulse response spectrum which facilitates subsequent data processing activities.
The seismic data recorded during vibroseis prospecting (hereinafter referred to as "vibrator data") is a composite signal consisting of many long reflected wavetrains superimposed upon one another. Since this composite signal is typically many times longer than the interval between reflections, it is not possible to distinguish individual reflections on the recorded signal. Thus, the first step in conventional processing of vibrator data is to cross-correlate the recorded data with the sweep signal. See e.g., Kirk, P., "Vibroseis Processing", Chapter 2 of Developments in Geophysical Exploration Methods--2, edited by A. Fitch, Applied Science Publishers Ltd., London, 1981, pp. 37-52. This cross-correlation compresses the length of the impulse response of the data from several seconds to tens of milliseconds so that the correlated data approximates the data that would have been recorded if the source had been an impulsive source. Following this cross-correlation, processing of the vibrator data may proceed in much the same manner as processing of data from an impulsive source.
The cross-correlation process has some undesirable consequences. The cross-correlated data represent the response of the earth to the autocorrelation of the input signal, rather than to the input signal itself. In other words, the cross-correlation process results in zero-phase data. Because of this, the data are no longer causal (i.e., having a definite inception in time), but are non-causal (i.e., the effects of a reflector will become evident even before the signal reaches it). Other processes commonly used in seismic data processing, such as dereverberation, assume causality, and the filters derived in these processes may be incorrect with respect to non-causal data. A second, practical limitation of the cross-correlation process is that a certain amount of tapering of the frequency spectrum of the vibroseis signal is necessary. Because the cross-correlation process squares the amplitude spectrum of the signal, the tapering is accentuated in the correlated data. This has the undesirable consequence, in the time domain, of producing a long, drawn out signal which tends to ring and makes interpretation of the data more difficult. Further, although the cross-correlation process does dramatically reduce the length of the impulse response of the data, further compression to more nearly approximate a true impulse would result in sharper, clearer seismic images with higher resolution than is currently possible with vibrator data.
From the foregoing, it can be seen that a need exists for a method of determining the impulse response of the earth in the processing of seismic vibrator data which overcomes the above-described problems resulting from the cross-correlation process.